Search engines may penalize sites they discover using black or grey hat methods, either by reducing their rankings or eliminating their listings from their databases altogether. Such penalties can be applied either automatically by the search engines' algorithms, or by a manual site review. One example was the February 2006 Google removal of both BMW Germany and Ricoh Germany for use of deceptive practices. Both companies, however, quickly apologized, fixed the offending pages, and were restored to Google's search engine results page.
Over the past year or two, we've also seen Google begin to fundamentally alter how its search algorithm works. Google, as with many of the tech giants, has begun to bill itself as an artificial intelligence (AI) and machine learning (ML) company rather than as a search company. AI tools will provide a way to spot anomalies in search results and collect insights. In essence, Google is changing what it considers its crown jewels. As the company builds ML into its entire product stack, its core search product has begun to behave a lot differently. This is heating up the cat-and-mouse game of SEO and sending the industry chasing after Google once again.
A variety of methods can increase the prominence of a webpage within the search results. Cross linking between pages of the same website to provide more links to important pages may improve its visibility. Writing content that includes frequently searched keyword phrase, so as to be relevant to a wide variety of search queries will tend to increase traffic. Updating content so as to keep search engines crawling back frequently can give additional weight to a site. Adding relevant keywords to a web page's metadata, including the title tag and meta description, will tend to improve the relevancy of a site's search listings, thus increasing traffic. URL canonicalization of web pages accessible via multiple URLs, using the canonical link element or via 301 redirects can help make sure links to different versions of the URL all count towards the page's link popularity score.
The caveat in all of this is that, in one way or another, most of the data and the rules governing what ranks and what doesn't (often on a week-to-week basis) comes from Google. If you know where to find and how to use the free and freemium tools Google provides under the surface—AdWords, Google Analytics, and Google Search Console being the big three—you can do all of this manually. Much of the data that the ongoing position monitoring, keyword research, and crawler tools provide is extracted in one form or another from Google itself. Doing it yourself is a disjointed, meticulous process, but you can piece together all the SEO data you need to come up with an optimization strategy should you be so inclined.
WebSite Auditor scans pages for code errors, duplicate content and other structure-related issues they may have. Other than that, there is this on-page optimization module, which allows determining the ideal keyword placement and researches page elements that can be optimized. In WebSite Auditor you can also analyze competitor’s pages to compare of to improve own on-page strategy. There are actually more features, I just won’t be listing all of them here. But this is the best solution with regard to on-page optimization I found so far.
SEOptimer is a free SEO Audit Tool that will perform a detailed SEO Analysis across 100 website data points, and provide clear and actionable recommendations for steps you can take to improve your online presence and ultimately rank better in Search Engine Results. SEOptimer is ideal for website owners, website designers and digital agencies who want to improve their own sites or theirs of their clients.
For example, let's say the keyword difficulty of a particular term is in the 80s and 90s in the top five spots on a particular search results page. Then, in positions 6-9, the difficulty scores drop down into the 50s and 60s. Using that difficulty score, a business can begin targeting that range of spots and running competitive analysis on the pages to see who your website could knock out of their spot.
A breadcrumb is a row of internal links at the top or bottom of the page that allows visitors to quickly navigate back to a previous section or the root page. Many breadcrumbs have the most general page (usually the root page) as the first, leftmost link and list the more specific sections out to the right. We recommend using breadcrumb structured data markup28 when showing breadcrumbs.
Structured data21 is code that you can add to your sites' pages to describe your content to search engines, so they can better understand what's on your pages. Search engines can use this understanding to display your content in useful (and eye-catching!) ways in search results. That, in turn, can help you attract just the right kind of customers for your business.
This helpful tool scans your backlink profile and turns up a list of contact information for the links and domains you'll need to reach out to for removal. Alternatively, the tool also allows you to export the list if you wish to disavow them using Google's tool. (Essentially, this tool tells Google not to take these links into account when crawling your site.)
The self-service keyword research tools we tested all handle pricing relatively similarly, pricing by month with discounts for annual billing with most SMB-focused plans ranging in the $50-$200 per month range. Depending on how your business plans to use the tools, the way particular products delineate pricing might make more sense. KWFinder.com is the cheapest of the bunch, but it's focused squarely on ad hoc keyword and Google SERP queries, which is why the product sets quotas for keyword lookups per 24 hours at different tiers. Moz and Ahrefs price by campaigns or projects, meaning the number of websites you're tracking in the dashboard. Most of the tools also cap the number of keyword reports you can run per day. SpyFu prices a bit differently, providing unlimited data access and results but capping the number of sales leads and domain contacts.
In 1998, two graduate students at Stanford University, Larry Page and Sergey Brin, developed "Backrub", a search engine that relied on a mathematical algorithm to rate the prominence of web pages. The number calculated by the algorithm, PageRank, is a function of the quantity and strength of inbound links. PageRank estimates the likelihood that a given page will be reached by a web user who randomly surfs the web, and follows links from one page to another. In effect, this means that some links are stronger than others, as a higher PageRank page is more likely to be reached by the random web surfer.